1. Field of the Disclosure
Generally, the present disclosure relates to the field of fabricating microstructures, such as integrated circuits, and, more particularly, to the transport characteristics of complex process tools, such as cluster tools, used for the fabrication of semiconductor devices or other microstructures.
2. Description of the Related Art
Today's global market forces manufacturers of mass products to offer high quality products at a low price. It is thus important to improve yield and process efficiency to minimize production costs. This holds especially true in the field of microstructure fabrication, for instance for manufacturing semiconductor devices, since, in this field, it is essential to combine cutting-edge technology with mass production techniques. It is, therefore, the goal of manufacturers of semiconductors, or generally of microstructures, to reduce the consumption of raw materials and consumables while at the same time improve process tool utilization. The latter aspect is especially important since, in modern semiconductor facilities, equipment is required which is extremely cost-intensive and represents the dominant part of the total production costs. At the same time, the process tools of the semiconductor facility have to be replaced more frequently compared to most other technical fields due to the rapid development of new products and processes, which may also demand correspondingly adapted process tools.
Integrated circuits are typically manufactured in automated or semi-automated facilities, thereby passing through a large number of process and metrology steps to complete the device. The number and the type of process steps and metrology steps a semiconductor device has to go through depends on the specifics of the semiconductor device to be fabricated. A usual process flow for an integrated circuit may include a plurality of photolithography steps to image a circuit pattern for a specific device layer into a resist layer, which is subsequently patterned to form a resist mask for further processes in structuring the device layer under consideration by, for example, etch or implant processes and the like. Thus, layer after layer, a plurality of process steps are performed based on a specific lithographic mask set for the various layers of the specified device. For instance, a sophisticated CPU requires several hundred process steps, each of which has to be carried out within specified process margins so as to fulfill the specifications for the device under consideration. As the majority of the process margins are device-specific, many of the metrology processes and the actual manufacturing processes are specifically designed for the device under consideration and require specific parameter settings at the adequate metrology and process tools.
In a semiconductor facility, a plurality of different product types are usually manufactured at the same time, such as memory chips of different design and storage capacity, CPUs of different design and operating speed and the like, wherein the number of different product types may even reach hundreds and more in production lines for manufacturing ASICs (application specific ICs). Since each of the different product types may require a specific process flow, possibly based on different mask sets for the lithography, specific settings in the various process tools, such as deposition tools, etch tools, implantation tools, chemical mechanical polishing (CMP) tools and the like, may be necessary. Consequently, a plurality of different tool parameter settings and product types may be encountered simultaneously in a manufacturing environment.
Hereinafter, the parameter setting for a specific process in a specified process tool or metrology or inspection tool may be commonly referred to as process recipe or simply as recipe. Thus, a large number of different process recipes, even for the same type of process tools, may be required which have to be applied to the process tools at the time the corresponding product types are to be processed in the respective tools. However, the sequence of process recipes performed in process and metrology tools, or in functionally combined equipment groups, as well as the recipes themselves, may have to be frequently altered due to fast product changes and highly variable processes involved. As a consequence, tool performance, especially in terms of throughput, is a very critical manufacturing parameter as it significantly affects the overall production costs of the individual devices. The progression of throughput over time of individual process and metrology tools, or even certain entities thereof, such as process modules, substrate robot handlers, load ports and the like, may, however, remain unobserved due to the complexity of the manufacturing sequences including a large number of product types and a corresponding large number of processes, which in turn are subjected to frequent recipe changes.
Recently, process tools have become more complex in that a process tool may include a plurality of functional modules or entities, referred to as cluster or cluster tool, which may operate in a parallel and/or sequential manner such that products arriving at the cluster tool may be operated therein in a plurality of process paths, depending on the process recipe and the current tool state. The cluster tool may enable the performance of a sequence of correlated processes, thereby enhancing overall efficiency by, for instance, reducing transport activities within the factory, and/or to increase tool capacity and availability by using several process chambers in parallel for the same process step. In a cluster tool, several modules or entities are typically served by one robot substrate handler, wherein the different process times, due to different recipes and the like, and/or the parallel processing in some of the modules, may result in competitive transport tasks, thereby generating a dynamic, i.e., a time-varying sequence of events. When several transport tasks are pending at a time, then the robot may operate on the basis of a predefined static rule in order to select an appropriate task for attempting to achieve a desired tool performance, such as maximum tool utilization and the like. This rule may prescribe, for example, to choose the substrate having experienced the least number of process steps from all the substrates requesting transport by the robot handler at this time, or to select the transport task having the destination with the highest predefined priority and the like. In many cases the transport sequencing rule is preselected, in view of tool utilization, such that the “bottleneck” module, i.e., the process module of the cluster tool having the least process capacity, is served so as to enable a substantially continuous operation, thereby typically producing a high tool utilization as long as substrates are available at the cluster tool.
In typical semiconductor facilities, the substrates are transported in groups, referred to as lots, within specific carriers designed to accommodate a specified number of substrates. As previously explained, many different types of products in different manufacturing stages may be present within the facility, such as test substrates, pilot substrates, special order devices and the like. Hence, the lots may have different sizes, i.e., the respective carriers are not completely filled, which may contribute significantly to a highly dynamic situation at the various process tools, since typically the minimum time for carrier exchange is independent from the number of substrates, whereas exchange time necessary for continuously keeping the process tool fed with substrates may vary significantly with lot size as a more frequent carrier exchange at a load port in combination with reduced process times required by a reduced number of substrates per lot may also reduce the time usable for exchanging a carrier substantially without negatively affecting the overall operation of the process tool. The time available for carrier exchange may be referred to as window of opportunity for carrier exchange and may represent a significant factor determining the overall performance of a process tool, in particular when a dynamic situation occurs at one or more process tools, for instances caused by the presence of different lot sizes. As discussed above, the process situation in a cluster tool may typically represent per se a dynamic situation, the degree of which may even be “amplified” in combination with an increased degree of variation in lot size. Under these conditions, the transport rules implemented in conventional cluster tools may result in a non-optimal tool performance.
The present disclosure is directed to various methods and systems that may solve, or at least reduce, some or all of the aforementioned problems.